Confirmatory factor analysis
Test a factor model you specified in advance.
When to use it
Use confirmatory factor analysis when you already claim that certain items measure a named factor. The model is a sentence such as F1 =~ q1 + q2 + q3 + q4. Fit indices say whether that claim is tolerable. To hunt for a structure, use exploratory factor analysis.
Assumptions
Indicators are numeric. Rows with a missing indicator are dropped. The model has to be identified: a factor with a single indicator, or too few indicators for the number of free loadings, will not fit. The first loading on a factor is fixed at 1 so the factor has a scale. Tensr does not offer an estimator menu.
Running it in Tensr
Options
Prop
Type
Reading the output
A one-factor model, Focus, measured by item1 to item4. Those four items share a moderate factor.
| Indicator | Factor | Estimate | Std. Err | p-value |
|---|---|---|---|---|
| item1 | Focus | 1 | — | — |
| item2 | Focus | 1.40438 | 0.425655 | p < .001 |
| item3 | Focus | 1.37948 | 0.418823 | p < .001 |
| item4 | Focus | 0.943559 | 0.319745 | p = .003 |
Confirmatory factor analysis with semopy fit indices. Confirmatory factor analysis with semopy fit indices. Metrics: CFI = 0.999; RMSEA = 0.014; SRMR = 0.04.
Reporting (APA 7)
Confirmatory factor analysis with semopy fit indices. Report the estimate in the table. This procedure is not summarised by one p-value.
Coming from SPSS
The product menu is Multivariate → CFA. SPSS itself fits this kind of model in Amos, not in the Analyze menu. The syntax is the same shape as lavaan: F1 =~ q1 + q2 + q3 + q4.